Update app.py

app.py

@@ -1,13 +1,14 @@
 import os
-import streamlit as st
-from PIL import Image
 import datetime
+from PIL import Image
+import gradio as gr
 
 # Folder paths
 INPUT_FOLDER = "./input/"
 OUTPUT_FOLDER = "./output/"
 LOG_FOLDER = "./logs/"
 PROCESSED_IMAGE = os.path.join(OUTPUT_FOLDER, "processed_image.png")
+LOG_FILE = os.path.join(LOG_FOLDER, "conversion_log.txt")
 
 # Ensure required folders exist
 os.makedirs(INPUT_FOLDER, exist_ok=True)
@@ -16,50 +17,56 @@ os.makedirs(LOG_FOLDER, exist_ok=True)
 
 # Function to log conversion steps
 def log_conversion(status, input_image, output_image):
-    log_path = os.path.join(LOG_FOLDER, "conversion_log.txt")
-    with open(log_path, "a") as log_file:
+    with open(LOG_FILE, "a") as log_file:
         log_file.write(f"{datetime.datetime.now()} - Status: {status}\n")
         log_file.write(f"Input Image: {input_image}\n")
         log_file.write(f"Output Image: {output_image}\n\n")
 
-# Streamlit app interface
-def main():
-    st.title("Image Grayscale Converter and Resizer")
+# Processing function
+def process_image(uploaded_image, new_width, new_height):
+    try:
+        # Save the uploaded image temporarily
+        input_image_path = os.path.join(INPUT_FOLDER, "uploaded_image.png")
+        uploaded_image.save(input_image_path)
+
+        # Open and process the image
+        with Image.open(input_image_path) as img:
+            grayscale_image = img.convert("L")  # Convert to grayscale
+            resized_image = grayscale_image.resize((int(new_width), int(new_height)))  # Resize
+            resized_image.save(PROCESSED_IMAGE)
+
+        # Log success
+        log_conversion("Success", input_image_path, PROCESSED_IMAGE)
+
+        # Return processed image and log file
+        return PROCESSED_IMAGE, LOG_FILE
+    except Exception as e:
+        log_conversion("Failed", "Uploaded Image", "Processing Error")
+        return None, f"Error: {str(e)}"
 
-    # File upload
-    uploaded_file = st.file_uploader("Upload your image file", type=["jpg", "jpeg", "png"])
-    if uploaded_file:
-        input_image_path = os.path.join(INPUT_FOLDER, uploaded_file.name)
-        with open(input_image_path, "wb") as f:
-            f.write(uploaded_file.read())
-        st.success(f"File uploaded: {uploaded_file.name}")
+# Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Image Grayscale Converter and Resizer")
 
-        # Display the uploaded image
-        st.image(input_image_path, caption="Uploaded Image", use_column_width=True)
+    with gr.Row():
+        image_input = gr.Image(type="pil", label="Upload Image")
+        with gr.Column():
+            width_input = gr.Number(value=800, label="Width (pixels)")
+            height_input = gr.Number(value=600, label="Height (pixels)")
 
-        # User controls for adjustments
-        new_width = st.number_input("Width (pixels)", value=800, step=10)
-        new_height = st.number_input("Height (pixels)", value=600, step=10)
+    process_button = gr.Button("Process Image")
 
-        # Process the file
-        if st.button("Process Image"):
-            try:
-                # Step 1: Open and process the image
-                with Image.open(input_image_path) as img:
-                    grayscale_image = img.convert("L")  # Convert to grayscale
-                    resized_image = grayscale_image.resize((new_width, new_height))  # Resize
-                    resized_image.save(PROCESSED_IMAGE)
+    with gr.Row():
+        image_output = gr.Image(label="Processed Image")
+        log_file_output = gr.File(label="Download Log File")
 
-                # Step 2: Log the process
-                log_conversion("Success", input_image_path, PROCESSED_IMAGE)
+    # Define the button click functionality
+    process_button.click(
+        process_image,
+        inputs=[image_input, width_input, height_input],
+        outputs=[image_output, log_file_output],
+    )
 
-                # Provide download link
-                st.success("Image processed successfully!")
-                st.image(PROCESSED_IMAGE, caption="Processed Image", use_column_width=True)
-                st.download_button("Download Processed Image", open(PROCESSED_IMAGE, "rb"), file_name="processed_image.png")
-            except Exception as e:
-                log_conversion("Failed", input_image_path, PROCESSED_IMAGE)
-                st.error(f"Error processing image: {e}")
+# Launch the app
+demo.launch()
 
-if __name__ == "__main__":
-    main()